{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3LRJZNE7DNNTLKF6BHDF7WTZNN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"80ff7d5711961400e75dfd9142f496fae11f2a7441fc3e944c9616510b58a89e","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-04-03T16:04:22Z","title_canon_sha256":"6037f808ec7a0cc042d1c36d0db0ea621d063b69542911b826c4a23bbd152edc"},"schema_version":"1.0","source":{"id":"1804.01050","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.01050","created_at":"2026-05-18T00:09:25Z"},{"alias_kind":"arxiv_version","alias_value":"1804.01050v3","created_at":"2026-05-18T00:09:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.01050","created_at":"2026-05-18T00:09:25Z"},{"alias_kind":"pith_short_12","alias_value":"3LRJZNE7DNNT","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3LRJZNE7DNNTLKF6","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3LRJZNE7","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:8724534d82bafa4d64e9734bfec2f8eb60b35899496230eb1368ece261c7d393","target":"graph","created_at":"2026-05-18T00:09:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Variational auto-encoders (VAEs) are a popular and powerful deep generative model. Previous works on VAEs have assumed a factorized likelihood model, whereby the output uncertainty of each pixel is assumed to be independent. This approximation is clearly limited as demonstrated by observing a residual image from a VAE reconstruction, which often possess a high level of structure. This paper demonstrates a novel scheme to incorporate a structured Gaussian likelihood prediction network within the VAE that allows the residual correlations to be modeled. Our novel architecture, with minimal increa","authors_text":"Gara Dorta, Ivor Simpson, Lourdes Agapito, Neill D.F. Campbell, Sara Vicente","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-04-03T16:04:22Z","title":"Training VAEs Under Structured Residuals"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.01050","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fafcf5fab60e6fbeb252f2c9c0d95f1185282dc7b8385b5bdabaf8b512230d6e","target":"record","created_at":"2026-05-18T00:09:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"80ff7d5711961400e75dfd9142f496fae11f2a7441fc3e944c9616510b58a89e","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-04-03T16:04:22Z","title_canon_sha256":"6037f808ec7a0cc042d1c36d0db0ea621d063b69542911b826c4a23bbd152edc"},"schema_version":"1.0","source":{"id":"1804.01050","kind":"arxiv","version":3}},"canonical_sha256":"dae29cb49f1b5b35a8be09c65fda796b6a605365e4f9c4c6243792830e6f3012","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dae29cb49f1b5b35a8be09c65fda796b6a605365e4f9c4c6243792830e6f3012","first_computed_at":"2026-05-18T00:09:25.374860Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:25.374860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qz4o5GjEaflRcV7rSM3Poo8U/CTmpLluaFyqln4Gfz6qfpGXZqFJONIrznhNwzhNYXboANAPL96d6uxp5aBBCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:25.375368Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.01050","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fafcf5fab60e6fbeb252f2c9c0d95f1185282dc7b8385b5bdabaf8b512230d6e","sha256:8724534d82bafa4d64e9734bfec2f8eb60b35899496230eb1368ece261c7d393"],"state_sha256":"a9221a9177a99f42c83ec8167bd2210ba6f4eb3c660c0206d290362d01552900"}